{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# python 作业\n",
    "## 作业要求\n",
    "绘制 sin 函数波形   \n",
    "使用了库 numpy   \n",
    "和 pylab\n",
    "## 代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import scipy as sp\n",
    "import pylab as pl\n",
    "x = np.linspace(0, 4*np.pi, 100)\n",
    "pl.plot( x, np.sin(x))\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
